Student Assistant / Master Thesis - Deep Learning for Urban Climate Emulation
Tasks
- Compare deep learning inference speed and accuracy with traditional CFD
- Develop and train deep learning emulators for 3D wind and temperature fields
- Evaluate model generalization capabilities
- Generate synthetic urban datasets using large eddy simulation
- Implement signed distance functions and gradients for building geometry
Perks/Benefits
Skills/Tech-stack
3D Data Representation | 3D data | Data representation | Deep learning | Differential Equations | Eddy Simulation | Fourier analysis | GPU Computing | Large Eddy Simulation | Neural Networks | Partial differential equations | PyTorch | Python | Signed Distance Function | TensorFlow
Education
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